Irrigation canals are large-scale systems, consisting of many
interacting components, and spanning vast geographical areas. For
safe and efficient operation of these canals, maintaining the levels
of the water flows close to pre-specified reference values is crucial,
both under normal operating conditions as well as in extreme situations.
Irrigation canals are equipped with local controllers, to control
the flow of water by adjusting the settings of control structures
such as gates and pumps. Traditionally, the local controllers
operate in a decentralized way in the sense that they use local
information only, that they are not explicitly aware of the
presence of other controllers or subsystems, and that no
communication among them takes place. Hence, an obvious drawback of
such a decentralized control scheme is that adequate performance at
a system-wide level may be jeopardized, due to the unexpected and
unanticipated interactions among the subsystems and the actions of
the local controllers.
In this paper we survey the state-of-the-art literature on
distributed control of water systems in general, and irrigation
canals in particular. We focus on the model predictive control
(MPC) strategy, which is a model-based control strategy in which
prediction models are used in an optimization to determine optimal
control inputs over a given horizon. We discuss how communication
among local MPC controllers can be included to improve the
performance of the overall system. We present a distributed
control scheme in which each controller employs MPC to determine
those actions that maintain water levels after disturbances close
to pre-specified reference values. Using the presented scheme the
local controllers cooperatively strive for obtaining the best
system-wide performance. A simulation study on an irrigation canal
with seven reaches illustrates the potential of the approach.